Using 64-bit storage to queue incoming transaction server requests

ABSTRACT

According to one embodiment, a method for queuing a transaction request. The method may include receiving, by a processor, at least one transaction request from a transaction processing system. The method may also include storing the at least one received transaction request in a queue within a 64-bit storage system. The method may further include monitoring a 31-bit storage system. The method may also include determining at least one control block within the monitored 31-bit storage system is available. The method may further include transmitting the at least one stored transaction request to the monitored 31-bit storage system.

BACKGROUND

The present invention relates generally to the field of computing, and more particularly to transaction processing.

Transaction processing may relate to the processing of information that is separated into individual, indivisible operations. Each operation, or transaction, can only be processed as a complete unit. A transaction may not be partially completed. For example, all three parts of a three part transaction must either succeed or fail together. The transaction may not have two of the three parts succeed while one part fails. Transaction processing systems may perform routine operations necessary to conduct business, such as sales order management, airline reservation systems, payroll systems, employee records systems, insurance systems, and shipping systems.

SUMMARY

According to one embodiment, a method for queuing a transaction request. The method may include receiving, by a processor, at least one transaction request from a transaction processing system. The method may also include storing the at least one received transaction request in a queue within a 64-bit storage system. The method may further include monitoring a 31-bit storage system. The method may also include determining at least one control block within the monitored 31-bit storage system is available. The method may further include transmitting the at least one stored transaction request to the monitored 31-bit storage system.

According to another embodiment, a computer system for queuing a transaction request. The computer system may include one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, whereby the computer system is capable of performing a method. The computer system may include receiving at least one transaction request from a transaction processing system. The computer system may also include storing the at least one received transaction request in a queue within a 64-bit storage system. The computer system may further include monitoring a 31-bit storage system. The computer system may also include determining at least one control block within the monitored 31-bit storage system is available. The computer system may further include transmitting the at least one stored transaction request to the monitored 31-bit storage system.

According to yet another embodiment, a computer program product for queuing a transaction request. The computer program product may include one or more computer-readable storage devices and program instructions stored on at least one of the one or more tangible storage devices, the program instructions executable by a processor. The computer program product may include program instructions to receive at least one transaction request from a transaction processing system. The computer program product may also include program instructions to store the at least one received transaction request in a queue within a 64-bit storage system. The computer program product may further include program instructions to monitor a 31-bit storage system. The computer program product may also include program instructions to determine at least one control block within the monitored 31-bit storage system is available. The computer program product may further include program instructions to transmit the at least one stored transaction request to the monitored 31-bit storage system.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

These and other objects, features and advantages of the present invention will become apparent from the following detailed description of illustrative embodiments thereof, which is to be read in connection with the accompanying drawings. The various features of the drawings are not to scale as the illustrations are for clarity in facilitating one skilled in the art in understanding the invention in conjunction with the detailed description.

FIG. 1 depicts an example multicore transactional memory environment, in accordance with an illustrative embodiment;

FIG. 2 depicts an example multicore transactional memory environment, in accordance with an illustrative embodiment;

FIG. 3 depicts example components of an example CPU, in accordance with an illustrative embodiment;

FIG. 4 is an exemplary networked computer environment, in accordance with one embodiment of the present invention;

FIG. 5 illustrates a flowchart of the operational steps carried out by a program to queue transaction requests in 64-bit memory storage, in accordance with one embodiment of the present invention;

FIG. 6 is a block diagram of internal and external components of computers and servers depicted in FIG. 4 according to at least one embodiment;

FIG. 7 depicts a cloud computing environment according to an embodiment of the present invention; and

FIG. 8 depicts abstraction model layers according to an embodiment of the present invention.

DETAILED DESCRIPTION

Detailed embodiments of the claimed structures and methods are disclosed herein; however, it can be understood that the disclosed embodiments are merely illustrative of the claimed structures and methods that may be embodied in various forms. This invention may, however, be embodied in many different forms and should not be construed as limited to the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete and will fully convey the scope of this invention to those skilled in the art. In the description, details of well-known features and techniques may be omitted to avoid unnecessarily obscuring the presented embodiments.

Embodiments of the present invention are related to the field of computing, and more particularly to transaction processing. The following described exemplary embodiments provide a system, method, and program product to, among other things, queue transaction requests into 64-bit storage when 31-bit storage is unavailable. Therefore, the present embodiment has the capacity to improve the technical field of transaction processing by moving a transaction request to 64-bit storage rather than relocating each control block from 31-bit storage to 64-bit storage. More specifically, moving transaction request to 64-bit storage when 31-bit storage is unavailable may efficiently use system resources as well as preserving system storage space and preventing system abending.

As previously described, transaction processing may relate to the processing of information that is separated into individual, indivisible operations. Each operation, or transaction, can only be processed as a complete unit. A transaction may not be partially completed. For example, all three parts of a three part transaction must either succeed or fail together. The transaction may not have two of the three parts succeed while one part fails. Transaction processing systems may perform routine operations necessary to conduct business, such as sales order management, airline reservation systems, payroll systems, employee records systems, insurance systems, and shipping systems.

Many transaction servers implement processing control blocks utilizing 31-bit storage. Processing control blocks, or control blocks, may relate to data structures that contains the information needed to manage a particular process in an operating system. When a transaction server receives a transaction request, the transaction request may be processed into 31-bit storage using the corresponding control blocks. However, since only a finite number of control blocks exist in 31-bit storage, a transaction server may reach capacity in 31-bit storage. As such, it may be advantageous, among other things, to implement a system that utilizes 64-bit storage control blocks to queue transaction requests when 31-bit storage reaches capacity until space within 31-bit storage is made available.

According to one embodiment, when a transaction server receives a transaction request when 31-bit storage is unavailable, such as when 31-bit storage has reached capacity and all control blocks are being used, the transaction server may move the transaction request to 64-bit storage and hold the transaction request in a queue within the 64-bit storage until control blocks within the 31-bit storage are made available. If a queue is created within the 64-bit storage, the transaction server may monitor the state of the 31-bit storage to check for newly freed control blocks. Once control blocks within the 31-bit storage are available, the transaction server may move the transaction request back to the 31-bit storage and process the transaction request.

By queuing transaction requests in 64-bit storage, additional control blocks may not need to be created within 31-bit storage. Therefore, alternations to the 31-bit storage code may not be needed. Furthermore, the addition of more control blocks to the 31-bit storage may not increase the transaction processing speed of the system. Additionally, if too many control blocks exist within the 31-bit storage, then address space may reach storage capacity and abend.

The present invention may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.

Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.

These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

Historically, a computer system or processor had only a single processor (aka processing unit or central processing unit). The processor included an instruction processing unit (IPU), a branch unit, a memory control unit and the like. Such processors were capable of executing a single thread of a program at a time. Operating systems were developed that could time-share a processor by dispatching a program to be executed on the processor for a period of time, and then dispatching another program to be executed on the processor for another period of time. As technology evolved, memory subsystem caches were often added to the processor as well as complex dynamic address translation including translation lookaside buffers (TLBs). The IPU itself was often referred to as a processor. As technology continued to evolve, an entire processor could be packaged on a single semiconductor chip or die, such a processor was referred to as a microprocessor. Then processors were developed that incorporated multiple IPUs, such processors were often referred to as multi-processors. Each such processor of a multi-processor computer system (processor) may include individual or shared caches, memory interfaces, system bus, address translation mechanism, and the like. Virtual machine and instruction set architecture (ISA) emulators added a layer of software to a processor, that provided the virtual machine with multiple “virtual processors” (aka processors) by time-slice usage of a single IPU in a single hardware processor. As technology further evolved, multi-threaded processors were developed, enabling a single hardware processor having a single multi-thread IPU to provide a capability of simultaneously executing threads of different programs, thus each thread of a multi-threaded processor appeared to the operating system as a processor. As technology further evolved, it was possible to put multiple processors (each having an IPU) on a single semiconductor chip or die. These processors were referred to processor cores or just cores. Thus the terms such as processor, central processing unit, processing unit, microprocessor, core, processor core, processor thread, and thread, for example, are often used interchangeably. Aspects of embodiments herein may be practiced by any or all processors including those shown supra, without departing from the teachings herein. Wherein the term “thread” or “processor thread” is used herein, it is expected that particular advantage of the embodiment may be had in a processor thread implementation.

Transaction Execution in Intel® Based Embodiments

In “Intel® Architecture Instruction Set Extensions Programming Reference” 319433-012A, February 2012, incorporated herein by reference in its entirety, Chapter 8 teaches, in part, that multithreaded applications may take advantage of increasing numbers of CPU cores to achieve higher performance. However, the writing of multi-threaded applications requires programmers to understand and take into account data sharing among the multiple threads. Access to shared data typically requires synchronization mechanisms. These synchronization mechanisms are used to ensure that multiple threads update shared data by serializing operations that are applied to the shared data, often through the use of a critical section that is protected by a lock. Since serialization limits concurrency, programmers try to limit the overhead due to synchronization.

Intel® Transactional Synchronization Extensions (Intel® TSX) allow a processor to dynamically determine whether threads need to be serialized through lock-protected critical sections, and to perform that serialization only when required. This allows the processor to expose and exploit concurrency that is hidden in an application because of dynamically unnecessary synchronization.

With Intel TSX, programmer-specified code regions (also referred to as “transactional regions” or just “transactions”) are executed transactionally. If the transactional execution completes successfully, then all memory operations performed within the transactional region will appear to have occurred instantaneously when viewed from other processors. A processor makes the memory operations of the executed transaction, performed within the transactional region, visible to other processors only when a successful commit occurs, i.e., when the transaction successfully completes execution. This process is often referred to as an atomic commit.

Intel TSX provides two software interfaces to specify regions of code for transactional execution. Hardware Lock Elision (HLE) is a legacy compatible instruction set extension (comprising the XACQUIRE and XRELEASE prefixes) to specify transactional regions. Restricted Transactional Memory (RTM) is a new instruction set interface (comprising the XBEGIN, XEND, and XABORT instructions) for programmers to define transactional regions in a more flexible manner than that possible with HLE. HLE is for programmers who prefer the backward compatibility of the conventional mutual exclusion programming model and would like to run HLE-enabled software on legacy hardware but would also like to take advantage of the new lock elision capabilities on hardware with HLE support. RTM is for programmers who prefer a flexible interface to the transactional execution hardware. In addition, Intel TSX also provides an XTEST instruction. This instruction allows software to query whether the logical processor is transactionally executing in a transactional region identified by either HLE or RTM.

Since a successful transactional execution ensures an atomic commit, the processor executes the code region optimistically without explicit synchronization. If synchronization was unnecessary for that specific execution, execution can commit without any cross-thread serialization. If the processor cannot commit atomically, then the optimistic execution fails. When this happens, the processor will roll back the execution, a process referred to as a transactional abort. On a transactional abort, the processor will discard all updates performed in the memory region used by the transaction, restore architectural state to appear as if the optimistic execution never occurred, and resume execution non-transactionally.

A processor can perform a transactional abort for numerous reasons. A primary reason to abort a transaction is due to conflicting memory accesses between the transactionally executing logical processor and another logical processor. Such conflicting memory accesses may prevent a successful transactional execution. Memory addresses read from within a transactional region constitute the read-set of the transactional region and addresses written to within the transactional region constitute the write-set of the transactional region. Intel TSX maintains the read and write-sets at the granularity of a cache line. A conflicting memory access occurs if another logical processor either reads a location that is part of the transactional region's write-set or writes a location that is a part of either the read or write-set of the transactional region. A conflicting access typically means that serialization is required for this code region. Since Intel TSX detects data conflicts at the granularity of a cache line, unrelated data locations placed in the same cache line will be detected as conflicts that result in transactional aborts. Transactional aborts may also occur due to limited transactional resources. For example, the amount of data accessed in the region may exceed an implementation-specific capacity. Additionally, some instructions and system events may cause transactional aborts. Frequent transactional aborts result in wasted cycles and increased inefficiency.

Hardware Lock Elision

Hardware Lock Elision (HLE) provides a legacy compatible instruction set interface for programmers to use transactional execution. HLE provides two new instruction prefix hints: XACQUIRE and XRELEASE.

With HLE, a programmer adds the XACQUIRE prefix to the front of the instruction that is used to acquire the lock that is protecting the critical section. The processor treats the prefix as a hint to elide the write associated with the lock acquire operation. Even though the lock acquire has an associated write operation to the lock, the processor does not add the address of the lock to the transactional region's write-set nor does it issue any write requests to the lock. Instead, the address of the lock is added to the read-set. The logical processor enters transactional execution. If the lock was available before the XACQUIRE prefixed instruction, then all other processors will continue to see the lock as available afterwards. Since the transactionally executing logical processor neither added the address of the lock to its write-set nor performed externally visible write operations to the lock, other logical processors can read the lock without causing a data conflict. This allows other logical processors to also enter and concurrently execute the critical section protected by the lock. The processor automatically detects any data conflicts that occur during the transactional execution and will perform a transactional abort if necessary.

Even though the eliding processor did not perform any external write operations to the lock, the hardware ensures program order of operations on the lock. If the eliding processor itself reads the value of the lock in the critical section, it will appear as if the processor had acquired the lock, i.e. the read will return the non-elided value. This behavior allows an HLE execution to be functionally equivalent to an execution without the HLE prefixes.

An XRELEASE prefix can be added in front of an instruction that is used to release the lock protecting a critical section. Releasing the lock involves a write to the lock. If the instruction is to restore the value of the lock to the value the lock had prior to the XACQUIRE prefixed lock acquire operation on the same lock, then the processor elides the external write request associated with the release of the lock and does not add the address of the lock to the write-set. The processor then attempts to commit the transactional execution.

With HLE, if multiple threads execute critical sections protected by the same lock but they do not perform any conflicting operations on each other's data, then the threads can execute concurrently and without serialization. Even though the software uses lock acquisition operations on a common lock, the hardware recognizes this, elides the lock, and executes the critical sections on the two threads without requiring any communication through the lock—if such communication was dynamically unnecessary.

If the processor is unable to execute the region transactionally, then the processor will execute the region non-transactionally and without elision. HLE enabled software has the same forward progress guarantees as the underlying non-HLE lock-based execution. For successful HLE execution, the lock and the critical section code must follow certain guidelines. These guidelines only affect performance; and failure to follow these guidelines will not result in a functional failure. Hardware without HLE support will ignore the XACQUIRE and XRELEASE prefix hints and will not perform any elision since these prefixes correspond to the REPNE/REPE IA-32 prefixes which are ignored on the instructions where XACQUIRE and XRELEASE are valid. Importantly, HLE is compatible with the existing lock-based programming model. Improper use of hints will not cause functional bugs though it may expose latent bugs already in the code.

Restricted Transactional Memory (RTM) provides a flexible software interface for transactional execution. RTM provides three new instructions—XBEGIN, XEND, and XABORT—for programmers to start, commit, and abort a transactional execution.

The programmer uses the XBEGIN instruction to specify the start of a transactional code region and the XEND instruction to specify the end of the transactional code region. If the RTM region could not be successfully executed transactionally, then the XBEGIN instruction takes an operand that provides a relative offset to the fallback instruction address.

A processor may abort RTM transactional execution for many reasons. In many instances, the hardware automatically detects transactional abort conditions and restarts execution from the fallback instruction address with the architectural state corresponding to that present at the start of the XBEGIN instruction and the EAX register updated to describe the abort status.

The XABORT instruction allows programmers to abort the execution of an RTM region explicitly. The XABORT instruction takes an 8-bit immediate argument that is loaded into the EAX register and will thus be available to software following an RTM abort. RTM instructions do not have any data memory location associated with them. While the hardware provides no guarantees as to whether an RTM region will ever successfully commit transactionally, most transactions that follow the recommended guidelines are expected to successfully commit transactionally. However, programmers must always provide an alternative code sequence in the fallback path to guarantee forward progress. This may be as simple as acquiring a lock and executing the specified code region non-transactionally. Further, a transaction that always aborts on a given implementation may complete transactionally on a future implementation. Therefore, programmers must ensure the code paths for the transactional region and the alternative code sequence are functionally tested.

Detection of HLE Support

A processor supports HLE execution if CPUID.07H.EBX.HLE [bit 4]=1. However, an application can use the HLE prefixes (XACQUIRE and XRELEASE) without checking whether the processor supports HLE. Processors without HLE support ignore these prefixes and will execute the code without entering transactional execution.

Detection of RTM Support

A processor supports RTM execution if CPUID.07H.EBX.RTM [bit 11]=1. An application must check if the processor supports RTM before it uses the RTM instructions (XBEGIN, XEND, XABORT). These instructions will generate a #UD exception when used on a processor that does not support RTM.

Detection of XTEST Instruction

A processor supports the XTEST instruction if it supports either HLE or RTM. An application must check either of these feature flags before using the XTEST instruction. This instruction will generate a #UD exception when used on a processor that does not support either HLE or RTM.

Querying Transactional Execution Status

The XTEST instruction can be used to determine the transactional status of a transactional region specified by HLE or RTM. Note, while the HLE prefixes are ignored on processors that do not support HLE, the XTEST instruction will generate a #UD exception when used on processors that do not support either HLE or RTM.

Requirements for HLE Locks

For HLE execution to successfully commit transactionally, the lock must satisfy certain properties and access to the lock must follow certain guidelines.

An XRELEASE prefixed instruction must restore the value of the elided lock to the value it had before the lock acquisition. This allows hardware to safely elide locks by not adding them to the write-set. The data size and data address of the lock release (XRELEASE prefixed) instruction must match that of the lock acquire (XACQUIRE prefixed) and the lock must not cross a cache line boundary.

Software should not write to the elided lock inside a transactional HLE region with any instruction other than an XRELEASE prefixed instruction, otherwise such a write may cause a transactional abort. In addition, recursive locks (where a thread acquires the same lock multiple times without first releasing the lock) may also cause a transactional abort. Note that software can observe the result of the elided lock acquire inside the critical section. Such a read operation will return the value of the write to the lock.

The processor automatically detects violations to these guidelines, and safely transitions to a non-transactional execution without elision. Since Intel TSX detects conflicts at the granularity of a cache line, writes to data collocated on the same cache line as the elided lock may be detected as data conflicts by other logical processors eliding the same lock.

Transactional Nesting

Both HLE and RTM support nested transactional regions. However, a transactional abort restores state to the operation that started transactional execution: either the outermost XACQUIRE prefixed HLE eligible instruction or the outermost XBEGIN instruction. The processor treats all nested transactions as one transaction.

HLE Nesting and Elision

Programmers can nest HLE regions up to an implementation specific depth of MAX_HLE_NEST_COUNT. Each logical processor tracks the nesting count internally but this count is not available to software. An XACQUIRE prefixed HLE-eligible instruction increments the nesting count, and an XRELEASE prefixed HLE-eligible instruction decrements it. The logical processor enters transactional execution when the nesting count goes from zero to one. The logical processor attempts to commit only when the nesting count becomes zero. A transactional abort may occur if the nesting count exceeds MAX_HLE_NEST_COUNT.

In addition to supporting nested HLE regions, the processor can also elide multiple nested locks. The processor tracks a lock for elision beginning with the XACQUIRE prefixed HLE eligible instruction for that lock and ending with the XRELEASE prefixed HLE eligible instruction for that same lock. The processor can, at any one time, track up to a MAX_HLE_ELIDED_LOCKS number of locks. For example, if the implementation supports a MAX_HLE_ELIDED_LOCKS value of two and if the programmer nests three HLE identified critical sections (by performing XACQUIRE prefixed HLE eligible instructions on three distinct locks without performing an intervening XRELEASE prefixed HLE eligible instruction on any one of the locks), then the first two locks will be elided, but the third won't be elided (but will be added to the transaction's writeset). However, the execution will still continue transactionally. Once an XRELEASE for one of the two elided locks is encountered, a subsequent lock acquired through the XACQUIRE prefixed HLE eligible instruction will be elided.

The processor attempts to commit the HLE execution when all elided XACQUIRE and XRELEASE pairs have been matched, the nesting count goes to zero, and the locks have satisfied requirements. If execution cannot commit atomically, then execution transitions to a non-transactional execution without elision as if the first instruction did not have an XACQUIRE prefix.

RTM Nesting

Programmers can nest RTM regions up to an implementation specific MAX_RTM_NEST_COUNT. The logical processor tracks the nesting count internally but this count is not available to software. An XBEGIN instruction increments the nesting count, and an XEND instruction decrements the nesting count. The logical processor attempts to commit only if the nesting count becomes zero. A transactional abort occurs if the nesting count exceeds MAX_RTM_NEST_COUNT.

Nesting HLE and RTM

HLE and RTM provide two alternative software interfaces to a common transactional execution capability. Transactional processing behavior is implementation specific when HLE and RTM are nested together, e.g., HLE is inside RTM or RTM is inside HLE. However, in all cases, the implementation will maintain HLE and RTM semantics. An implementation may choose to ignore HLE hints when used inside RTM regions, and may cause a transactional abort when RTM instructions are used inside HLE regions. In the latter case, the transition from transactional to non-transactional execution occurs seamlessly since the processor will re-execute the HLE region without actually doing elision, and then execute the RTM instructions.

Abort Status Definition

RTM uses the EAX register to communicate abort status to software. Following an RTM abort the EAX register has the following definition.

TABLE 1 RTM Abort Status Definition EAX Register Bit Position Meaning 0 Set if abort caused by XABORT instruction 1 If set, the transaction may succeed on retry, this bit is always clear if bit 0 is set 2 Set if another logical processor conflicted with a memory address that was part of the transaction that aborted 3 Set if an internal buffer overflowed 4 Set if a debug breakpoint was hit 5 Set if an abort occurred during execution of a nested transaction 23:6 Reserved 31-24 XABORT argument (only valid if bit 0 set, otherwise reserved)

The EAX abort status for RTM only provides causes for aborts. It does not by itself encode whether an abort or commit occurred for the RTM region. The value of EAX can be 0 following an RTM abort. For example, a CPUID instruction when used inside an RTM region causes a transactional abort and may not satisfy the requirements for setting any of the EAX bits. This may result in an EAX value of 0.

RTM Memory Ordering

A successful RTM commit causes all memory operations in the RTM region to appear to execute atomically. A successfully committed RTM region consisting of an XBEGIN followed by an XEND, even with no memory operations in the RTM region, has the same ordering semantics as a LOCK prefixed instruction.

The XBEGIN instruction does not have fencing semantics. However, if an RTM execution aborts, then all memory updates from within the RTM region are discarded and are not made visible to any other logical processor.

RTM-Enabled Debugger Support

By default, any debug exception inside an RTM region will cause a transactional abort and will redirect control flow to the fallback instruction address with architectural state recovered and bit 4 in EAX set. However, to allow software debuggers to intercept execution on debug exceptions, the RTM architecture provides additional capability.

If bit 11 of DR7 and bit 15 of the IA32_DEBUGCTL_MSR are both 1, any RTM abort due to a debug exception (#DB) or breakpoint exception (#BP) causes execution to roll back and restart from the XBEGIN instruction instead of the fallback address. In this scenario, the EAX register will also be restored back to the point of the XBEGIN instruction.

Programming Considerations

Typical programmer-identified regions are expected to transactionally execute and commit successfully. However, Intel TSX does not provide any such guarantee. A transactional execution may abort for many reasons. To take full advantage of the transactional capabilities, programmers should follow certain guidelines to increase the probability of their transactional execution committing successfully.

This section discusses various events that may cause transactional aborts. The architecture ensures that updates performed within a transaction that subsequently aborts execution will never become visible. Only committed transactional executions initiate an update to the architectural state. Transactional aborts never cause functional failures and only affect performance.

Instruction Based Considerations

Programmers can use any instruction safely inside a transaction (HLE or RTM) and can use transactions at any privilege level. However, some instructions will always abort the transactional execution and cause execution to seamlessly and safely transition to a non-transactional path.

Intel TSX allows for most common instructions to be used inside transactions without causing aborts. The following operations inside a transaction do not typically cause an abort:

-   -   Operations on the instruction pointer register, general purpose         registers (GPRs) and the status flags (CF, OF, SF, PF, AF, and         ZF); and     -   Operations on XMM and YMM registers and the MXCSR register.

However, programmers must be careful when intermixing SSE and AVX operations inside a transactional region. Intermixing SSE instructions accessing XMM registers and AVX instructions accessing YMM registers may cause transactions to abort. Programmers may use REP/REPNE prefixed string operations inside transactions. However, long strings may cause aborts. Further, the use of CLD and STD instructions may cause aborts if they change the value of the DF flag. However, if DF is 1, the STD instruction will not cause an abort. Similarly, if DF is 0, then the CLD instruction will not cause an abort.

Instructions not enumerated here as causing abort when used inside a transaction will typically not cause a transaction to abort (examples include but are not limited to MFENCE, LFENCE, SFENCE, RDTSC, RDTSCP, etc.).

The following instructions will abort transactional execution on any implementation:

-   -   XABORT     -   CPUID     -   PAUSE

In addition, in some implementations, the following instructions may always cause transactional aborts. These instructions are not expected to be commonly used inside typical transactional regions. However, programmers must not rely on these instructions to force a transactional abort, since whether they cause transactional aborts is implementation dependent.

-   -   Operations on X87 and MMX architecture state. This includes all         MMX and X87 instructions, including the FXRSTOR and FXSAVE         instructions.     -   Update to non-status portion of EFLAGS: CLI, STI, POPFD, POPFQ,         CLTS.     -   Instructions that update segment registers, debug registers         and/or control registers:     -   MOV to DS/ES/FS/GS/SS, POP DS/ES/FS/GS/SS, LDS, LES, LFS, LGS,         LSS, SWAPGS, WRFSBASE, WRGSBASE, LGDT, SGDT, LIDT, SIDT, LLDT,         SLDT, LTR, STR, Far CALL, Far JMP, Far RET, IRET, MOV to DRx,         MOV to CR0/CR2/CR3/CR4/CR8 and LMSW.     -   Ring transitions: SYSENTER, SYSCALL, SYSEXIT, and SYSRET.     -   TLB and Cacheability control: CLFLUSH, INVD, WBINVD, INVLPG,         INVPCID, and memory instructions with a non-temporal hint         (MOVNTDQA, MOVNTDQ, MOVNTI, MOVNTPD, MOVNTPS, and MOVNTQ).     -   Processor state save: XSAVE, XSAVEOPT, and XRSTOR.     -   Interrupts: INTn, INTO.     -   IO: IN, INS, REP INS, OUT, OUTS, REP OUTS and their variants.     -   VMX: VMPTRLD, VMPTRST, VMCLEAR, VMREAD, VMWRITE, VMCALL,         VMLAUNCH, VMRESUME, VMXOFF, VMXON, INVEPT, and INVVPID.     -   SMX: GETSEC.     -   UD2, RSM, RDMSR, WRMSR, HLT, MONITOR, MWAIT, XSETBV, VZEROUPPER,         MASKMOVQ, and V/MASKMOVDQU.

Runtime Considerations

In addition to the instruction-based considerations, runtime events may cause transactional execution to abort. These may be due to data access patterns or micro-architectural implementation features. The following list is not a comprehensive discussion of all abort causes.

Any fault or trap in a transaction that must be exposed to software will be suppressed. Transactional execution will abort and execution will transition to a non-transactional execution, as if the fault or trap had never occurred. If an exception is not masked, then that un-masked exception will result in a transactional abort and the state will appear as if the exception had never occurred.

Synchronous exception events (#DE, #OF, #NP, #SS, #GP, #BR, #UD, #AC, #XF, #PF, #NM, #TS, #MF, #DB, #BP/INT3) that occur during transactional execution may cause an execution not to commit transactionally, and require a non-transactional execution. These events are suppressed as if they had never occurred. With HLE, since the non-transactional code path is identical to the transactional code path, these events will typically re-appear when the instruction that caused the exception is re-executed non-transactionally, causing the associated synchronous events to be delivered appropriately in the non-transactional execution. Asynchronous events (NMI, SMI, INTR, IPI, PMI, etc.) occurring during transactional execution may cause the transactional execution to abort and transition to a non-transactional execution. The asynchronous events will be pended and handled after the transactional abort is processed.

Transactions only support write-back cacheable memory type operations. A transaction may always abort if the transaction includes operations on any other memory type. This includes instruction fetches to UC memory type.

Memory accesses within a transactional region may require the processor to set the Accessed and Dirty flags of the referenced page table entry. The behavior of how the processor handles this is implementation specific. Some implementations may allow the updates to these flags to become externally visible even if the transactional region subsequently aborts. Some Intel TSX implementations may choose to abort the transactional execution if these flags need to be updated. Further, a processor's page-table walk may generate accesses to its own transactionally written but uncommitted state. Some Intel TSX implementations may choose to abort the execution of a transactional region in such situations. Regardless, the architecture ensures that, if the transactional region aborts, then the transactionally written state will not be made architecturally visible through the behavior of structures such as TLBs.

Executing self-modifying code transactionally may also cause transactional aborts. Programmers must continue to follow the Intel recommended guidelines for writing self-modifying and cross-modifying code even when employing HLE and RTM. While an implementation of RTM and HLE will typically provide sufficient resources for executing common transactional regions, implementation constraints and excessive sizes for transactional regions may cause a transactional execution to abort and transition to a non-transactional execution. The architecture provides no guarantee of the amount of resources available to do transactional execution and does not guarantee that a transactional execution will ever succeed.

Conflicting requests to a cache line accessed within a transactional region may prevent the transaction from executing successfully. For example, if logical processor P0 reads line A in a transactional region and another logical processor P1 writes line A (either inside or outside a transactional region) then logical processor P0 may abort if logical processor P1's write interferes with processor P0's ability to execute transactionally.

Similarly, if P0 writes line A in a transactional region and P1 reads or writes line A (either inside or outside a transactional region), then P0 may abort if P1's access to line A interferes with P0's ability to execute transactionally. In addition, other coherence traffic may at times appear as conflicting requests and may cause aborts. While these false conflicts may happen, they are expected to be uncommon. The conflict resolution policy to determine whether P0 or P1 aborts in the above scenarios is implementation specific.

Generic Transaction Execution Embodiments:

According to “ARCHITECTURES FOR TRANSACTIONAL MEMORY”, a dissertation submitted to the Department of Computer Science and the Committee on Graduate Studies of Stanford University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy, by Austen McDonald, June 2009, incorporated by reference herein in its entirety, fundamentally, there are three mechanisms needed to implement an atomic and isolated transactional region: versioning, conflict detection, and contention management.

To make a transactional code region appear atomic, all the modifications performed by that transactional code region must be stored and kept isolated from other transactions until commit time. The system does this by implementing a versioning policy. Two versioning paradigms exist: eager and lazy. An eager versioning system stores newly generated transactional values in place and stores previous memory values on the side, in what is called an undo-log. A lazy versioning system stores new values temporarily in what is called a write buffer, copying them to memory only on commit. In either system, the cache is used to optimize storage of new versions.

To ensure that transactions appear to be performed atomically, conflicts must be detected and resolved. The two systems, i.e., the eager and lazy versioning systems, detect conflicts by implementing a conflict detection policy, either optimistic or pessimistic. An optimistic system executes transactions in parallel, checking for conflicts only when a transaction commits. A pessimistic system checks for conflicts at each load and store. Similar to versioning, conflict detection also uses the cache, marking each line as either part of the read-set, part of the write-set, or both. The two systems resolve conflicts by implementing a contention management policy. Many contention management policies exist, some are more appropriate for optimistic conflict detection and some are more appropriate for pessimistic. Described below are some example policies.

Since each transactional memory (TM) system needs both versioning detection and conflict detection, these options give rise to four distinct TM designs: Eager-Pessimistic (EP), Eager-Optimistic (EO), Lazy-Pessimistic (LP), and Lazy-Optimistic (LO). Table 2 briefly describes all four distinct TM designs.

FIGS. 1 and 2 depict an example of a multicore TM environment. FIG. 1 shows many TM-enabled CPUs (CPU1 114 a, CPU2 114 b, etc.) on one die 100, connected with an interconnect 122, under management of an interconnect control 120 a, 120 b. Each CPU 114 a, 114 b (also known as a Processor) may have a split cache consisting of an Instruction Cache 116 a, 116 b for caching instructions from memory to be executed and a Data Cache 118 a, 118 b with TM support for caching data (operands) of memory locations to be operated on by CPU 114 a, 114 b (in FIG. 1, each CPU 114 a, 114 b and its associated caches are referenced as 112 a, 112 b). In an implementation, caches of multiple dies 100 are interconnected to support cache coherency between the caches of the multiple dies 100. In an implementation, a single cache, rather than the split cache is employed holding both instructions and data. In implementations, the CPU caches are one level of caching in a hierarchical cache structure. For example each die 100 may employ a shared cache 124 to be shared amongst all the CPUs on the die 100. In another implementation, each die may have access to a shared cache 124, shared amongst all the processors of all the dies 100.

FIG. 2 shows the details of an example transactional CPU environment 112, having a CPU 114, including additions to support TM. The transactional CPU (processor) 114 may include hardware for supporting Register Checkpoints 126 and special TM Registers 128. The transactional CPU cache may have the MESI bits 130, Tags 140 and Data 142 of a conventional cache but also, for example, R bits 132 showing a line has been read by the CPU 114 while executing a transaction and W bits 138 showing a line has been written-to by the CPU 114 while executing a transaction.

A key detail for programmers in any TM system is how non-transactional accesses interact with transactions. By design, transactional accesses are screened from each other using the mechanisms above. However, the interaction between a regular, non-transactional load with a transaction containing a new value for that address must still be considered. In addition, the interaction between a non-transactional store with a transaction that has read that address must also be explored. These are issues of the database concept isolation.

A TM system is said to implement strong isolation, sometimes called strong atomicity, when every non-transactional load and store acts like an atomic transaction. Therefore, non-transactional loads cannot see uncommitted data and non-transactional stores cause atomicity violations in any transactions that have read that address. A system where this is not the case is said to implement weak isolation, sometimes called weak atomicity.

Strong isolation is often more desirable than weak isolation due to the relative ease of conceptualization and implementation of strong isolation. Additionally, if a programmer has forgotten to surround some shared memory references with transactions, causing bugs, then with strong isolation, the programmer will often detect that oversight using a simple debug interface because the programmer will see a non-transactional region causing atomicity violations. Also, programs written in one model may work differently on another model. Further, strong isolation is often easier to support in hardware TM than weak isolation. With strong isolation, since the coherence protocol already manages load and store communication between processors, transactions can detect non-transactional loads and stores and act appropriately. To implement strong isolation in software Transactional Memory (TM), non-transactional code must be modified to include read and write-barriers; potentially crippling performance. Although great effort has been expended to remove many un-needed barriers, such techniques are often complex and performance is typically far lower than that of HTMs.

TABLE 2 Transactional Memory Design Space VERSIONING Lazy Eager CON- Optimis- Storing updates in Not practical: waiting to FLICT tic a write buffer; update memory until DETEC- detecting conflicts commit time but detecting TION at commit time. conflicts at access time guarantees wasted work and provides no advantage Pessimis- Storing updates in a Updating memory, keeping tic writebuffer; detect- old values in undo log; ing conflicts at detecting conflicts at access time. access time.

Table 2 illustrates the fundamental design space of transactional memory (versioning and conflict detection).

Eager-Pessimistic (EP)

This first TM design described below is known as Eager-Pessimistic. An EP system stores its write-set “in place” (hence the name “eager”) and, to support rollback, stores the old values of overwritten lines in an “undo log”. Processors use the W 138 and R 132 cache bits to track read and write-sets and detect conflicts when receiving snooped load requests. Perhaps the most notable examples of EP systems in known literature are LogTM and UTM.

Beginning a transaction in an EP system is much like beginning a transaction in other systems: tm_begin( ) takes a register checkpoint, and initializes any status registers. An EP system also requires initializing the undo log, the details of which are dependent on the log format, but often involve initializing a log base pointer to a region of pre-allocated, thread-private memory, and clearing a log bounds register.

Versioning: In EP, due to the way eager versioning is designed to function, the MESI 130 state transitions (cache line indicators corresponding to Modified, Exclusive, Shared, and Invalid code states) are left mostly unchanged. Outside of a transaction, the MESI 130 state transitions are left completely unchanged. When reading a line inside a transaction, the standard coherence transitions apply (S (Shared)→S, I (Invalid)→S, or I→E (Exclusive)), issuing a load miss as needed, but the R 132 bit is also set. Likewise, writing a line applies the standard transitions (S→M, E→I, I→M), issuing a miss as needed, but also sets the W 138 (Written) bit. The first time a line is written, the old version of the entire line is loaded then written to the undo log to preserve it in case the current transaction aborts. The newly written data is then stored “in-place,” over the old data.

Conflict Detection: Pessimistic conflict detection uses coherence messages exchanged on misses, or upgrades, to look for conflicts between transactions. When a read miss occurs within a transaction, other processors receive a load request; but they ignore the request if they do not have the needed line. If the other processors have the needed line non-speculatively or have the line R 132 (Read), they downgrade that line to S, and in certain cases issue a cache-to-cache transfer if they have the line in MESI's 130 M or E state. However, if the cache has the line W 138, then a conflict is detected between the two transactions and additional action(s) must be taken.

Similarly, when a transaction seeks to upgrade a line from shared to modified (on a first write), the transaction issues an exclusive load request, which is also used to detect conflicts. If a receiving cache has the line non-speculatively, then the line is invalidated, and in certain cases a cache-to-cache transfer (M or E states) is issued. But, if the line is R 132 or W 138, a conflict is detected.

Validation: Because conflict detection is performed on every load, a transaction always has exclusive access to its own write-set. Therefore, validation does not require any additional work.

Commit: Since eager versioning stores the new version of data items in place, the commit process simply clears the W 138 and R 132 bits and discards the undo log.

Abort: When a transaction rolls back, the original version of each cache line in the undo log must be restored, a process called “unrolling” or “applying” the log. This is done during tm_discard( ) and must be atomic with regard to other transactions. Specifically, the write-set must still be used to detect conflicts: this transaction has the only correct version of lines in its undo log, and requesting transactions must wait for the correct version to be restored from that log. Such a log can be applied using a hardware state machine or software abort handler.

Eager-Pessimistic has the characteristics of: Commit is simple and since it is in-place, very fast. Similarly, validation is a no-op. Pessimistic conflict detection detects conflicts early, thereby reducing the number of “doomed” transactions. For example, if two transactions are involved in a Write-After-Read dependency, then that dependency is detected immediately in pessimistic conflict detection. However, in optimistic conflict detection such conflicts are not detected until the writer commits.

Eager-Pessimistic also has the characteristics of: As described above, the first time a cache line is written, the old value must be written to the log, incurring extra cache accesses. Aborts are expensive as they require undoing the log. For each cache line in the log, a load must be issued, perhaps going as far as main memory before continuing to the next line. Pessimistic conflict detection also prevents certain serializable schedules from existing.

Additionally, because conflicts are handled as they occur, there is a potential for livelock and careful contention management mechanisms must be employed to guarantee forward progress.

Lazy-Optimistic (LO)

Another popular TM design is Lazy-Optimistic (LO), which stores its write-set in a “write buffer” or “redo log” and detects conflicts at commit time (still using the R 132 and W 138 bits).

Versioning: Just as in the EP system, the MESI protocol of the LO design is enforced outside of the transactions. Once inside a transaction, reading a line incurs the standard MESI transitions but also sets the R 132 bit. Likewise, writing a line sets the W 138 bit of the line, but handling the MESI transitions of the LO design is different from that of the EP design. First, with lazy versioning, the new versions of written data are stored in the cache hierarchy until commit while other transactions have access to old versions available in memory or other caches. To make available the old versions, dirty lines (M lines) must be evicted when first written by a transaction. Second, no upgrade misses are needed because of the optimistic conflict detection feature: if a transaction has a line in the S state, it can simply write to it and upgrade that line to an M state without communicating the changes with other transactions because conflict detection is done at commit time.

Conflict Detection and Validation: To validate a transaction and detect conflicts, LO communicates the addresses of speculatively modified lines to other transactions only when it is preparing to commit. On validation, the processor sends one, potentially large, network packet containing all the addresses in the write-set. Data is not sent, but left in the cache of the committer and marked dirty (M). To build this packet without searching the cache for lines marked W, a simple bit vector is used, called a “store buffer,” with one bit per cache line to track these speculatively modified lines. Other transactions use this address packet to detect conflicts: if an address is found in the cache and the R 132 and/or W 138 bits are set, then a conflict is initiated. If the line is found but neither R 132 nor W 138 is set, then the line is simply invalidated, which is similar to processing an exclusive load.

To support transaction atomicity, these address packets must be handled atomically, i.e., no two address packets may exist at once with the same addresses. In an LO system, this can be achieved by simply acquiring a global commit token before sending the address packet. However, a two-phase commit scheme could be employed by first sending out the address packet, collecting responses, enforcing an ordering protocol (perhaps oldest transaction first), and committing once all responses are satisfactory.

Commit: Once validation has occurred, commit needs no special treatment: simply clear W 138 and R 132 bits and the store buffer. The transaction's writes are already marked dirty in the cache and other caches' copies of these lines have been invalidated via the address packet. Other processors can then access the committed data through the regular coherence protocol.

Abort: Rollback is equally easy: because the write-set is contained within the local caches, these lines can be invalidated, then clear W 138 and R 132 bits and the store buffer. The store buffer allows W lines to be found to invalidate without the need to search the cache.

Lazy-Optimistic has the characteristics of: Aborts are very fast, requiring no additional loads or stores and making only local changes. More serializable schedules can exist than found in EP, which allows an LO system to more aggressively speculate that transactions are independent, which can yield higher performance. Finally, the late detection of conflicts can increase the likelihood of forward progress.

Lazy-Optimistic also has the characteristics of: Validation takes global communication time proportional to size of write set. Doomed transactions can waste work since conflicts are detected only at commit time.

Lazy-Pessimistic (LP)

Lazy-Pessimistic (LP) represents a third TM design option, sitting somewhere between EP and LO: storing newly written lines in a write buffer but detecting conflicts on a per access basis.

Versioning: Versioning is similar but not identical to that of LO: reading a line sets its R bit 132, writing a line sets its W bit 138, and a store buffer is used to track W lines in the cache. Also, dirty (M) lines must be evicted when first written by a transaction, just as in LO. However, since conflict detection is pessimistic, load exclusives must be performed when upgrading a transactional line from I, S→M, which is unlike LO.

Conflict Detection: LP's conflict detection operates the same as EP's: using coherence messages to look for conflicts between transactions.

Validation: Like in EP, pessimistic conflict detection ensures that at any point, a running transaction has no conflicts with any other running transaction, so validation is a no-op.

Commit: Commit needs no special treatment: simply clear W 138 and R 132 bits and the store buffer, like in LO.

Abort: Rollback is also like that of LO: simply invalidate the write-set using the store buffer and clear the W and R bits and the store buffer.

Eager-Optimistic (EO)

The LP has the characteristics of: Like LO, aborts are very fast. Like EP, the use of pessimistic conflict detection reduces the number of “doomed” transactions. Like EP, some serializable schedules are not allowed and conflict detection must be performed on each cache miss.

The final combination of versioning and conflict detection is Eager-Optimistic (EO). EO may be a less than optimal choice for HTM systems: since new transactional versions are written in-place, other transactions have no choice but to notice conflicts as they occur (i.e., as cache misses occur). But since EO waits until commit time to detect conflicts, those transactions become “zombies,” continuing to execute, wasting resources, yet are “doomed” to abort.

EO has proven to be useful in STMs and is implemented by Bartok-STM and McRT. A lazy versioning STM needs to check its write buffer on each read to ensure that it is reading the most recent value. Since the write buffer is not a hardware structure, this is expensive, hence the preference for write-in-place eager versioning. Additionally, since checking for conflicts is also expensive in an STM, optimistic conflict detection offers the advantage of performing this operation in bulk.

Contention Management

How a transaction rolls back once the system has decided to abort that transaction has been described above, but, since a conflict involves two transactions, the topics of which transaction should abort, how that abort should be initiated, and when should the aborted transaction be retried need to be explored. These are topics that are addressed by Contention Management (CM), a key component of transactional memory. Described below are policies regarding how the systems initiate aborts and the various established methods of managing which transactions should abort in a conflict.

Contention Management Policies

A Contention Management (CM) Policy is a mechanism that determines which transaction involved in a conflict should abort and when the aborted transaction should be retried. For example, it is often the case that retrying an aborted transaction immediately does not lead to the best performance. Conversely, employing a back-off mechanism, which delays the retrying of an aborted transaction, can yield better performance. STMs first grappled with finding the best contention management policies and many of the policies outlined below were originally developed for STMs.

CM Policies draw on a number of measures to make decisions, including ages of the transactions, size of read and write-sets, the number of previous aborts, etc. The combinations of measures to make such decisions are endless, but certain combinations are described below, roughly in order of increasing complexity.

To establish some nomenclature, first note that in a conflict there are two sides: the attacker and the defender. The attacker is the transaction requesting access to a shared memory location. In pessimistic conflict detection, the attacker is the transaction issuing the load or load exclusive. In optimistic, the attacker is the transaction attempting to validate. The defender in both cases is the transaction receiving the attacker's request.

An Aggressive CM Policy immediately and always retries either the attacker or the defender. In LO, Aggressive means that the attacker always wins, and so Aggressive is sometimes called committer wins. Such a policy was used for the earliest LO systems. In the case of EP, Aggressive can be either defender wins or attacker wins.

Restarting a conflicting transaction that will immediately experience another conflict is bound to waste work—namely interconnect bandwidth refilling cache misses. A Polite CM Policy employs exponential backoff (but linear could also be used) before restarting conflicts. To prevent starvation, a situation where a process does not have resources allocated to it by the scheduler, the exponential backoff greatly increases the odds of transaction success after some n retries.

Another approach to conflict resolution is to randomly abort the attacker or defender (a policy called Randomized). Such a policy may be combined with a randomized backoff scheme to avoid unneeded contention.

However, making random choices, when selecting a transaction to abort, can result in aborting transactions that have completed “a lot of work”, which can waste resources. To avoid such waste, the amount of work completed on the transaction can be taken into account when determining which transaction to abort. One measure of work could be a transaction's age. Other methods include Oldest, Bulk TM, Size Matters, Karma, and Polka. Oldest is a simple timestamp method that aborts the younger transaction in a conflict. Bulk TM uses this scheme. Size Matters is like Oldest but instead of transaction age, the number of read/written words is used as the priority, reverting to Oldest after a fixed number of aborts. Karma is similar, using the size of the write-set as priority. Rollback then proceeds after backing off a fixed amount of time. Aborted transactions keep their priorities after being aborted (hence the name Karma). Polka works like Karma but instead of backing off a predefined amount of time, it backs off exponentially more each time.

Since aborting wastes work, it is logical to argue that stalling an attacker until the defender has finished their transaction would lead to better performance. Unfortunately, such a simple scheme easily leads to deadlock.

Deadlock avoidance techniques can be used to solve this problem. Greedy uses two rules to avoid deadlock. The first rule is, if a first transaction, T1, has lower priority than a second transaction, T0, or if T1 is waiting for another transaction, then T1 aborts when conflicting with T0. The second rule is, if T1 has higher priority than T0 and is not waiting, then T0 waits until T1 commits, aborts, or starts waiting (in which case the first rule is applied). Greedy provides some guarantees about time bounds for executing a set of transactions. One EP design (LogTM) uses a CM policy similar to Greedy to achieve stalling with conservative deadlock avoidance.

Example MESI coherency rules provide for four possible states in which a cache line of a multiprocessor cache system may reside, M, E, S, and I, defined as follows:

Modified (M): The cache line is present only in the current cache, and is dirty; it has been modified from the value in main memory. The cache is required to write the data back to main memory at some time in the future, before permitting any other read of the (no longer valid) main memory state. The write-back changes the line to the Exclusive state.

Exclusive (E): The cache line is present only in the current cache, but is clean; it matches main memory. It may be changed to the Shared state at any time, in response to a read request. Alternatively, it may be changed to the Modified state when writing to it.

Shared (S): Indicates that this cache line may be stored in other caches of the machine and is “clean”; it matches the main memory. The line may be discarded (changed to the Invalid state) at any time.

Invalid (I): Indicates that this cache line is invalid (unused).

TM coherency status indicators (R 132, W 138) may be provided for each cache line, in addition to, or encoded in the MESI coherency bits. An R 132 indicator indicates the current transaction has read from the data of the cache line, and a W 138 indicator indicates the current transaction has written to the data of the cache line.

In another aspect of TM design, a system is designed using transactional store buffers. U.S. Pat. No. 6,349,361 titled “Methods and Apparatus for Reordering and Renaming Memory References in a Multiprocessor Computer System,” filed Mar. 31, 2000 and incorporated by reference herein in its entirety, teaches a method for reordering and renaming memory references in a multiprocessor computer system having at least a first and a second processor. The first processor has a first private cache and a first buffer, and the second processor has a second private cache and a second buffer. The method includes the steps of, for each of a plurality of gated store requests received by the first processor to store a datum, exclusively acquiring a cache line that contains the datum by the first private cache, and storing the datum in the first buffer. Upon the first buffer receiving a load request from the first processor to load a particular datum, the particular datum is provided to the first processor from among the data stored in the first buffer based on an in-order sequence of load and store operations. Upon the first cache receiving a load request from the second cache for a given datum, an error condition is indicated and a current state of at least one of the processors is reset to an earlier state when the load request for the given datum corresponds to the data stored in the first buffer.

The main implementation components of one such transactional memory facility are a transaction-backup register file for holding pre-transaction GR (general register) content, a cache directory to track the cache lines accessed during the transaction, a store cache to buffer stores until the transaction ends, and firmware routines to perform various complex functions. In this section a detailed implementation is described.

IBM zEnterprise EC12 Enterprise Server Embodiment

The IBM zEnterprise EC12 enterprise server introduces transactional execution (TX) in transactional memory, and is described in part in a paper, “Transactional Memory Architecture and Implementation for IBM System z” of Proceedings Pages 25-36 presented at MICRO-45, 1-5 Dec. 2012, Vancouver, British Columbia, Canada, available from IEEE Computer Society Conference Publishing Services (CPS), which is incorporated by reference herein in its entirety.

Table 3 shows an example transaction. Transactions started with TBEGIN are not assured to ever successfully complete with TEND, since they can experience an aborting condition at every attempted execution, e.g., due to repeating conflicts with other CPUs. This requires that the program support a fallback path to perform the same operation non-transactionally, e.g., by using traditional locking schemes. This puts significant burden on the programming and software verification teams, especially where the fallback path is not automatically generated by a reliable compiler.

TABLE 3 Example Transaction Code LHI R0,0 *initialize retry count=0 loop TBEGIN *begin transaction JNZ abort *go to abort code if CC1=0 LT R1, lock *load and test the fallback lock JNZ lckbzy *branch if lock busy . . . perform operation . . . TEND *end transaction . . . . . . . . . . . . lckbzy TABORT *abort if lock busy; this *resumes after TBEGIN abort JO fallback *no retry if CC=3 AHI R0, 1 *increment retry count CIJNL R0,6, fallback *give up after 6 attempts PPA R0, TX *random delay based on retry count . . . potentially wait for lock to become free . . . J loop *jump back to retry fallback OBTAIN lock *using Compare&Swap . . . perform operation . . . RELEASE lock . . . . . . . . . . . .

The requirement of providing a fallback path for aborted Transaction Execution (TX) transactions can be onerous. Many transactions operating on shared data structures are expected to be short, touch only a few distinct memory locations, and use simple instructions only. For those transactions, the IBM zEnterprise EC12 introduces the concept of constrained transactions; under normal conditions, the CPU 114 (FIG. 2) assures that constrained transactions eventually end successfully, albeit without giving a strict limit on the number of necessary retries. A constrained transaction starts with a TBEGINC instruction and ends with a regular TEND. Implementing a task as a constrained or non-constrained transaction typically results in very comparable performance, but constrained transactions simplify software development by removing the need for a fallback path. IBM's Transactional Execution architecture is further described in z/Architecture, Principles of Operation, Tenth Edition, SA22-7832-09 published September 2012 from IBM, incorporated by reference herein in its entirety.

A constrained transaction starts with the TBEGINC instruction. A transaction initiated with TBEGINC must follow a list of programming constraints; otherwise the program takes a non-filterable constraint-violation interruption. Exemplary constraints may include, but not be limited to: the transaction can execute a maximum of 32 instructions, all instruction text must be within 256 consecutive bytes of memory; the transaction contains only forward-pointing relative branches (i.e., no loops or subroutine calls); the transaction can access a maximum of 4 aligned octowords (an octoword is 32 bytes) of memory; and restriction of the instruction-set to exclude complex instructions like decimal or floating-point operations. The constraints are chosen such that many common operations like doubly linked list-insert/delete operations can be performed, including the very powerful concept of atomic compare-and-swap targeting up to 4 aligned octowords. At the same time, the constraints were chosen conservatively such that future CPU implementations can assure transaction success without needing to adjust the constraints, since that would otherwise lead to software incompatibility.

TBEGINC mostly behaves like XBEGIN in TSX or TBEGIN on IBM's zEC12 servers, except that the floating-point register (FPR) control and the program interruption filtering fields do not exist and the controls are considered to be zero. On a transaction abort, the instruction address is set back directly to the TBEGINC instead of to the instruction after, reflecting the immediate retry and absence of an abort path for constrained transactions.

Nested transactions are not allowed within constrained transactions, but if a TBEGINC occurs within a non-constrained transaction it is treated as opening a new non-constrained nesting level just like TBEGIN would. This can occur, e.g., if a non-constrained transaction calls a subroutine that uses a constrained transaction internally. Since interruption filtering is implicitly off, all exceptions during a constrained transaction lead to an interruption into the operating system (OS). Eventual successful finishing of the transaction relies on the capability of the OS to page-in the at most 4 pages touched by any constrained transaction. The OS must also ensure time-slices long enough to allow the transaction to complete.

TABLE 4 Transaction Code Example TBEGINC *begin constrained transaction . . . perform operation . . . TEND *end transaction

Table 4 shows the constrained-transactional implementation of the code in Table 3, assuming that the constrained transactions do not interact with other locking-based code. No lock testing is shown therefore, but could be added if constrained transactions and lock-based code were mixed.

When failure occurs repeatedly, software emulation is performed using millicode as part of system firmware. Advantageously, constrained transactions have desirable properties because of the burden removed from programmers.

With reference to FIG. 3, the IBM zEnterprise EC12 processor introduced the transactional execution facility. The processor can decode 3 instructions per clock cycle; simple instructions are dispatched as single micro-ops, and more complex instructions are cracked into multiple micro-ops. The micro-ops (Uops 232 b) are written into a unified issue queue 216, from where they can be issued out-of-order. Up to two fixed-point, one floating-point, two load/store, and two branch instructions can execute every cycle. A Global Completion Table (GCT) 232 holds every micro-op 232 b and a transaction nesting depth (TND) 232 a. The GCT 232 is written in-order at decode time, tracks the execution status of each micro-op 232 b, and completes instructions when all micro-ops 232 b of the oldest instruction group have successfully executed.

The level 1 (L1) data cache 240 is a 96 KB (kilo-byte) 6-way associative cache with 256 byte cache-lines and 4 cycle use latency, coupled to a private 1 MB (mega-byte) 8-way associative 2nd-level (L2) data cache 268 with 7 cycles use-latency penalty for L1 240 misses. The L1 240 cache is the cache closest to a processor and Ln cache is a cache at the nth level of caching. Both L1 240 and L2 268 caches are store-through. Six cores on each central processor (CP) chip share a 48 MB 3rd-level store-in cache, and six CP chips are connected to an off-chip 384 MB 4th-level cache, packaged together on a glass ceramic multi-chip module (MCM). Up to 4 multi-chip modules (MCMs) can be connected to a coherent symmetric multi-processor (SMP) system with up to 144 cores (not all cores are available to run customer workload).

Coherency is managed with a variant of the MESI protocol. Cache-lines can be owned read-only (shared) or exclusive; the L1 240 and L2 268 are store-through and thus do not contain dirty lines. The L3 272 and L4 caches (not shown) are store-in and track dirty states. Each cache is inclusive of all its connected lower level caches.

Coherency requests are called “cross interrogates” (XI) and are sent hierarchically from higher level to lower-level caches, and between the L4s. When one core misses the L1 240 and L2 268 and requests the cache line from its local L3 272, the L3 272 checks whether it owns the line, and if necessary sends an XI to the currently owning L2 268/L1 240 under that L3 272 to ensure coherency, before it returns the cache line to the requestor. If the request also misses the L3 272, the L3 272 sends a request to the L4 (not shown), which enforces coherency by sending XIs to all necessary L3s 272 under that L4, and to the neighboring L4s. Then the L4 responds to the requesting L3 272 which forwards the response to the L2 268/L1 240.

Note that due to the inclusivity rule of the cache hierarchy, sometimes cache lines are XI'ed from lower-level caches due to evictions on higher-level caches caused by associativity overflows from requests to other cache lines. These XIs can be called “LRU XIs”, where LRU stands for least recently used.

Making reference to yet another type of XI requests, Demote-XIs transition cache-ownership from exclusive into read-only state, and Exclusive-XIs transition cache ownership from exclusive into invalid state. Demote-XIs and Exclusive-XIs need a response back to the XI sender. The target cache can “accept” the XI, or send a “reject” response if it first needs to evict dirty data before accepting the XI. The L1 240/L2 268 caches are store through, but may reject demote-XIs and exclusive XIs if they have stores in their store queues that need to be sent to L3 272 before downgrading the exclusive state. A rejected XI will be repeated by the sender. Read-only-XIs are sent to caches that own the line read-only; no response is needed for such XIs since they cannot be rejected. The details of the SMP protocol are similar to those described for the IBM z10 by P. Mak, C. Walters, and G. Strait, in “IBM System z10 processor cache subsystem microarchitecture”, IBM Journal of Research and Development, Vol 53:1, 2009, which is incorporated by reference herein in its entirety.

Transactional Instruction Execution

FIG. 3 depicts example components of an example transactional execution environment, including a CPU and caches/components with which it interacts (such as those depicted in FIGS. 1 and 2). The instruction decode unit 208 (IDU) keeps track of the current transaction nesting depth 212 (TND). When the IDU 208 receives a TBEGIN instruction, the nesting depth 212 is incremented, and conversely decremented on TEND instructions. The nesting depth 212 is written into the GCT 232 for every dispatched instruction. When a TBEGIN or TEND is decoded on a speculative path that later gets flushed, the IDU's 208 nesting depth 212 is refreshed from the youngest GCT 232 entry that is not flushed. The transactional state is also written into the issue queue 216 for consumption by the execution units, mostly by the Load/Store Unit (LSU) 280, which also has an effective address calculator 236 is included in the LSU 280. The TBEGIN instruction may specify a transaction diagnostic block (TDB) for recording status information, should the transaction abort before reaching a TEND instruction.

Similar to the nesting depth, the IDU 208/GCT 232 collaboratively track the access register/floating-point register (AR/FPR) modification masks through the transaction nest; the IDU 208 can place an abort request into the GCT 232 when an AR/FPR-modifying instruction is decoded and the modification mask blocks that. When the instruction becomes next-to-complete, completion is blocked and the transaction aborts. Other restricted instructions are handled similarly, including TBEGIN if decoded while in a constrained transaction, or exceeding the maximum nesting depth.

An outermost TBEGIN is cracked into multiple micro-ops depending on the GR-Save-Mask; each micro-op 232 b (including, for example, uop 0, uop 1, and uop 2) will be executed by one of the two fixed point units (FXUs) 220 to save a pair of GRs 228 into a special transaction-backup register file 224, that is used to later restore the GR 228 content in case of a transaction abort. Also the TBEGIN spawns micro-ops 232 b to perform an accessibility test for the TDB if one is specified; the address is saved in a special purpose register for later usage in the abort case. At the decoding of an outermost TBEGIN, the instruction address and the instruction text of the TBEGIN are also saved in special purpose registers for a potential abort processing later on.

TEND and NTSTG are single micro-op 232 b instructions; NTSTG (non-transactional store) is handled like a normal store except that it is marked as non-transactional in the issue queue 216 so that the LSU 280 can treat it appropriately. TEND is a no-op at execution time, the ending of the transaction is performed when TEND completes.

As mentioned, instructions that are within a transaction are marked as such in the issue queue 216, but otherwise execute mostly unchanged; the LSU 280 performs isolation tracking as described in the next section.

Since decoding is in-order, and since the IDU 208 keeps track of the current transactional state and writes it into the issue queue 216 along with every instruction from the transaction, execution of TBEGIN, TEND, and instructions before, within, and after the transaction can be performed out-of-order. It is even possible (though unlikely) that TEND is executed first, then the entire transaction, and lastly the TBEGIN executes. Program order is restored through the GCT 232 at completion time. The length of transactions is not limited by the size of the GCT 232, since general purpose registers (GRs) 228 can be restored from the backup register file 224.

During execution, the program event recording (PER) events are filtered based on the Event Suppression Control, and a PER TEND event is detected if enabled. Similarly, while in transactional mode, a pseudo-random generator may be causing the random aborts as enabled by the Transaction Diagnostics Control.

Tracking for Transactional Isolation

The Load/Store Unit 280 tracks cache lines that were accessed during transactional execution, and triggers an abort if an XI from another CPU (or an LRU-XI) conflicts with the footprint. If the conflicting XI is an exclusive or demote XI, the LSU 280 rejects the XI back to the L3 272 in the hope of finishing the transaction before the L3 272 repeats the XI. This “stiff-arming” is very efficient in highly contended transactions. In order to prevent hangs when two CPUs stiff-arm each other, a XI-reject counter is implemented, which triggers a transaction abort when a threshold is met.

The L1 cache directory 240 is traditionally implemented with static random access memories (SRAMs). For the transactional memory implementation, the valid bits 244 (64 rows×6 ways) of the directory have been moved into normal logic latches, and are supplemented with two more bits per cache line: the TX-read 248 and TX-dirty 252 bits.

The TX-read 248 bits are reset when a new outermost TBEGIN is decoded (which is interlocked against a prior still pending transaction). The TX-read 248 bit is set at execution time by every load instruction that is marked “transactional” in the issue queue. Note that this can lead to over-marking if speculative loads are executed, for example on a mispredicted branch path. The alternative of setting the TX-read 248 bit at load completion time was too expensive for silicon area, since multiple loads can complete at the same time, requiring many read-ports on the load-queue.

Stores execute the same way as in non-transactional mode, but a transaction mark is placed in the store queue (STQ) 260 entry of the store instruction. At write-back time, when the data from the STQ 260 is written into the L1 240, the TX-dirty bit 252 in the L1-directory 256 is set for the written cache line. Store write-back into the L1 240 occurs only after the store instruction has completed, and at most one store is written back per cycle. Before completion and write-back, loads can access the data from the STQ 260 by means of store-forwarding; after write-back, the CPU 114 (FIG. 2) can access the speculatively updated data in the L1 240. If the transaction ends successfully, the TX-dirty bits 252 of all cache-lines are cleared, and also the TX-marks of not yet written stores are cleared in the STQ 260, effectively turning the pending stores into normal stores.

On a transaction abort, all pending transactional stores are invalidated from the STQ 260, even those already completed. All cache lines that were modified by the transaction in the L1 240, that is, have the TX-dirty bit 252 on, have their valid bits turned off, effectively removing them from the L1 240 cache instantaneously.

The architecture requires that before completing a new instruction, the isolation of the transaction read and write-set is maintained. This isolation is ensured by stalling instruction completion at appropriate times when XIs are pending; speculative out-of-order execution is allowed, optimistically assuming that the pending XIs are to different addresses and not actually cause a transaction conflict. This design fits very naturally with the XI-vs-completion interlocks that are implemented on prior systems to ensure the strong memory ordering that the architecture requires.

When the L1 240 receives an XI, L1 240 accesses the directory to check validity of the XI'ed address in the L1 240, and if the TX-read bit 248 is active on the XI'ed line and the XI is not rejected, the LSU 280 triggers an abort. When a cache line with active TX-read bit 248 is LRU'ed from the L1 240, a special LRU-extension vector remembers for each of the 64 rows of the L1 240 that a TX-read line existed on that row. Since no precise address tracking exists for the LRU extensions, any non-rejected XI that hits a valid extension row the LSU 280 triggers an abort. Providing the LRU-extension effectively increases the read footprint capability from the L1-size to the L2-size and associativity, provided no conflicts with other CPUs 114 (FIGS. 1 and 2) against the non-precise LRU-extension tracking causes aborts.

The store footprint is limited by the store cache size (the store cache is discussed in more detail below) and thus implicitly by the L2 268 size and associativity. No LRU-extension action needs to be performed when a TX-dirty 252 cache line is LRU'ed from the L1 240.

Store Cache

In prior systems, since the L1 240 and L2 268 are store-through caches, every store instruction causes an L3 272 store access; with now 6 cores per L3 272 and further improved performance of each core, the store rate for the L3 272 (and to a lesser extent for the L2 268) becomes problematic for certain workloads. In order to avoid store queuing delays, a gathering store cache 264 had to be added, that combines stores to neighboring addresses before sending them to the L3 272.

For transactional memory performance, it is acceptable to invalidate every TX-dirty 252 cache line from the L1 240 on transaction aborts, because the L2 268 cache is very close (7 cycles L1 240 miss penalty) to bring back the clean lines. However, it would be unacceptable for performance (and silicon area for tracking) to have transactional stores write the L2 268 before the transaction ends and then invalidate all dirty L2 268 cache lines on abort (or even worse on the shared L3 272).

The two problems of store bandwidth and transactional memory store handling can both be addressed with the gathering store cache 264. The cache 264 is a circular queue of 64 entries, each entry holding 128 bytes of data with byte-precise valid bits. In non-transactional operation, when a store is received from the LSU 280, the store cache 264 checks whether an entry exists for the same address, and if so gathers the new store into the existing entry. If no entry exists, a new entry is written into the queue, and if the number of free entries falls under a threshold, the oldest entries are written back to the L2 268 and L3 272 caches.

When a new outermost transaction begins, all existing entries in the store cache are marked closed so that no new stores can be gathered into them, and eviction of those entries to L2 268 and L3 272 is started. From that point on, the transactional stores coming out of the LSU 280 and STQ 260 allocate new entries, or gather into existing transactional entries. The write-back of those stores into L2 268 and L3 272 is blocked, until the transaction ends successfully; at that point subsequent (post-transaction) stores can continue to gather into existing entries, until the next transaction closes those entries again.

The store cache 264 is queried on every exclusive or demote XI, and causes an XI reject if the XI compares to any active entry. If the core is not completing further instructions while continuously rejecting XIs, the transaction is aborted at a certain threshold to avoid hangs.

The LSU 280 requests a transaction abort when the store cache 264 overflows. The LSU 280 detects this condition when it tries to send a new store that cannot merge into an existing entry, and the entire store cache 264 is filled with stores from the current transaction. The store cache 264 is managed as a subset of the L2 268: while transactionally dirty lines can be evicted from the L1 240, they have to stay resident in the L2 268 throughout the transaction. The maximum store footprint is thus limited to the store cache size of 64×128 bytes, and it is also limited by the associativity of the L2 268. Since the L2 268 is 8-way associative and has 512 rows, it is typically large enough to not cause transaction aborts.

If a transaction aborts, the store cache 264 is notified and all entries holding transactional data are invalidated. The store cache 264 also has a mark per doubleword (8 bytes) whether the entry was written by a NTSTG instruction—those doublewords stay valid across transaction aborts.

Millicode-Implemented Functions

Traditionally, IBM mainframe server processors contain a layer of firmware called millicode which performs complex functions like certain CISC instruction executions, interruption handling, system synchronization, and RAS. Millicode includes machine dependent instructions as well as instructions of the instruction set architecture (ISA) that are fetched and executed from memory similarly to instructions of application programs and the operating system (OS). Firmware resides in a restricted area of main memory that customer programs cannot access. When hardware detects a situation that needs to invoke millicode, the instruction fetching unit 204 switches into “millicode mode” and starts fetching at the appropriate location in the millicode memory area. Millicode may be fetched and executed in the same way as instructions of the instruction set architecture (ISA), and may include ISA instructions.

For transactional memory, millicode is involved in various complex situations. Every transaction abort invokes a dedicated millicode sub-routine to perform the necessary abort steps. The transaction-abort millicode starts by reading special-purpose registers (SPRs) holding the hardware internal abort reason, potential exception reasons, and the aborted instruction address, which millicode then uses to store a TDB if one is specified. The TBEGIN instruction text is loaded from an SPR to obtain the GR-save-mask, which is needed for millicode to know which GRs 228 to restore.

The CPU 114 (FIG. 2) supports a special millicode-only instruction to read out the backup-GRs 224 and copy them into the main GRs 228. The TBEGIN instruction address is also loaded from an SPR to set the new instruction address in the PSW to continue execution after the TBEGIN once the millicode abort sub-routine finishes. That PSW may later be saved as program-old PSW in case the abort is caused by a non-filtered program interruption.

The TABORT instruction may be millicode implemented; when the IDU 208 decodes TABORT, it instructs the instruction fetch unit to branch into TABORT's millicode, from which millicode branches into the common abort sub-routine.

The Extract Transaction Nesting Depth (ETND) instruction may also be millicoded, since it is not performance critical; millicode loads the current nesting depth out of a special hardware register and places it into a GR 228. The PPA instruction is millicoded; it performs the optimal delay based on the current abort count provided by software as an operand to PPA, and also based on other hardware internal state.

For constrained transactions, millicode may keep track of the number of aborts. The counter is reset to 0 on successful TEND completion, or if an interruption into the OS occurs (since it is not known if or when the OS will return to the program). Depending on the current abort count, millicode can invoke certain mechanisms to improve the chance of success for the subsequent transaction retry. The mechanisms involve, for example, successively increasing random delays between retries, and reducing the amount of speculative execution to avoid encountering aborts caused by speculative accesses to data that the transaction is not actually using. As a last resort, millicode can broadcast to other CPUs 114 (FIG. 2) to stop all conflicting work, retry the local transaction, before releasing the other CPUs 114 (FIG. 2) to continue normal processing. Multiple CPUs 114 (FIG. 2) must be coordinated to not cause deadlocks, so some serialization between millicode instances on different CPUs 114 (FIG. 2) is required.

The following described exemplary embodiments provide a system, method, and program product to queue transaction requests in 64-bit storage when 31-bit storage control blocks are otherwise unavailable for processing newly received transaction requests.

Referring now to FIG. 4, an exemplary networked computer environment 400 is depicted, in accordance with one embodiment. The networked computer environment 400 may include client computing device 410 and server 420 interconnected via communication network 430. According to at least one implementation, networked computer environment 400 may include a plurality of client computing devices 410 and server 420, only one of each being shown for illustrative brevity.

Communication network 430 may include various types of communication networks, such as a wide area network (WAN), local area network (LAN), a telecommunication network, a wireless network, a public switched network and/or a satellite network. It may be appreciated that FIG. 4 provides only an illustration of one implementation and does not imply any limitations with regard to the environments in which different embodiments may be implemented. Many modifications to the depicted environments may be made based on design and implementation requirements.

Client computing device 410 may include processor 404 and data storage device 406 that is enabled to run software program 408, and communicate with server 420 via network 430, in accordance with one embodiment of the invention. Client computing device 410 may be, for example, a mobile device, a telephone, a personal digital assistant, a netbook, a laptop computer, a tablet computer, a desktop computer, or any type of computing device capable of running a program and accessing a network. As will be discussed with reference to FIG. 6, client computing device 410 may include internal components 602 a and external components 604 a, respectively.

Server computer 420, or database server, may be a laptop computer, netbook computer, personal computer (PC), a desktop computer, or any programmable electronic device capable of hosting transaction queuing program 412 and communicating with client computing device 410 via network 430, in accordance with embodiments of the invention. As will be discussed with reference to FIG. 6, server computer 420 may include internal components 602 b and external components 604 b, respectively. Server 420 may also operate in a cloud computing service model, such as Software as a Service (SaaS), Platform as a Service (PaaS), or Infrastructure as a Service (IaaS). Server 420 may also be located in a cloud computing deployment model, such as a private cloud, community cloud, public cloud, or hybrid cloud.

According to the present embodiment, transaction queuing program 412 may be a program capable of queuing transaction requests in 64-bit storage when 31-bit storage is otherwise unavailable. Transaction queuing program 412 is explained in further detail below with respect to FIG. 5.

Referring now to FIG. 5, a flowchart 500 of the operational steps carried out by a program to queue transaction requests in 64-bit memory storage is depicted, in accordance with one embodiment of the present invention. At 502, transaction queuing program 412 (FIG. 4) receives a transaction request from a client device 410 (FIG. 4). Transaction processing systems, such as sales order management systems, airline reservation systems, payroll systems, employee records systems, banking systems, insurance systems, and shipping systems, on client computing devices, such as client computing device 410 (FIG. 4), may transmit transaction requests to transaction servers, such as transaction server 420 (FIG. 4), when a user interacts with the system. For example, if a user purchases a product in an online marketplace using a credit card, a transaction request may be sent to transaction server 420 (FIG. 4) in order to process the user's purchase by transferring funds from the credit card company to the online retailer.

Next at 504, transaction queuing program 412 (FIG. 4) determines whether 31-bit storage is available in order to process the received transaction request. According to one implementation, the method may continue along operational flowchart 500, if 31-bit storage within transaction server 420 (FIG. 4) is unavailable. If transaction queuing program 412 (FIG. 4) determines 31-bit storage is available (step 504, “YES” branch), transaction queuing program 412 (FIG. 4) may continue to step 506 to process the received transaction request using available 31-bit storage control blocks. If transaction queuing program 412 (FIG. 4) determines 31-bit storage is unavailable (step 504, “NO” branch), transaction queuing program 412 (FIG. 4) may continue to step 508 to store the received transaction request within 64-bit storage.

Then at 506, transaction queuing program 412 (FIG. 4) processes the received transaction request using available 31-bit storage control blocks. As previously described, many transaction servers utilize 31-bit storage control blocks to process received transaction requests. When 31-bit storage control blocks are available, transaction queuing program 412 (FIG. 4) may immediately process the received transaction request using the 31-bit storage control blocks. For example, when a transaction request is received for a user's online purchase of a product from an online retailer and 31-bit storage control blocks are available, transaction queuing program 412 (FIG. 4) may immediately process the transaction request by debiting the user's credit card and crediting the online retailer's account.

Next at 508, transaction queuing program 412 (FIG. 4) stores the received transaction request in 64-bit storage. If transaction queuing program 412 (FIG. 4) determines insufficient 31-bit storage control blocks are available to process the received transaction request, transaction queuing program 412 (FIG. 4) may store the received transaction request in 64-bit storage. Since moving all 31-bit control blocks used for processing transactions to 64-bit storage may be inefficient and extremely time consuming, transaction queuing program 412 (FIG. 4) may create a queue of received transaction requests in 64-bit storage when insufficient control blocks within 31-bit storage are available. For example, in the previously described example of a user's purchase from an online retailer, the received transaction request may require more 31-bit storage control blocks than are currently available within the 31-bit storage system. Therefore, the transaction request corresponding to the user's purchase from the online retailer may be stored within the 64-bit storage system.

Then at 510, transaction queuing program 412 (FIG. 4) monitors the 31-bit storage system for available control blocks. Since actual processing of the stored transaction requests is to be conducted within the 31-bit storage system, transaction queuing program 412 (FIG. 4) may monitor the 31-bit storage system for available control blocks. For example, the 31-bit storage system may be unavailable because all control blocks are being used for the processing of transaction requests. Therefore, transaction queuing program 412 (FIG. 4) may queue additional transaction requests in 64-bit storage. Transaction queuing program 412 (FIG. 4) may then monitor the status of the 31-bit storage system for freed control blocks that may be used to process the queued transaction requests in 64-bit storage.

Next at 512, transaction queuing program 412 (FIG. 4) determines whether 31-bit storage is available. According to one implementation, the method may continue along operational flowchart 500, if 31-bit storage within transaction server 420 (FIG. 4) is available. If transaction queuing program 412 (FIG. 4) determines 31-bit storage is available (step 512, “YES” branch), transaction queuing program 412 (FIG. 4) may continue to step 514 to transmit the transaction request stored in the 64-bit storage system to the 31-bit storage system. If transaction queuing program 412 (FIG. 4) determines 31-bit storage is unavailable (step 512, “NO” branch), transaction queuing program 412 (FIG. 4) may return to step 510 to monitor the 31-bit storage system for available control blocks.

Then at 514, transaction queuing program 412 (FIG. 4) transmits the transaction request stored in the 64-bit storage system to the 31-bit storage system. Once control blocks within 31-bit storage become available, transaction queuing program 412 (FIG. 4) may move the stored transaction requests from the queue within 64-bit storage to the 31-bit storage. Transaction queuing program 412 (FIG. 4) may transmit the stored transaction request that are queued within the 64-bit storage system based on the total storage time for each stored transaction request. For example, if two transaction requests are stored within 64-bit storage awaiting processing within 31-bit storage, transaction queuing program 412 (FIG. 4) may transmit the stored transaction request to the 31-bit storage system that has been queued within the 64-bit storage for the longest period of time. In another embodiment of the present invention, transaction queuing program 412 (FIG. 4) may transmit the stored transaction requests based on the number of control blocks available within the 31-bit storage system. For example, two transaction requests, such as transaction request A and transaction request B, may be stored within 64-bit storage awaiting processing within the 31-bit storage. Transaction request A may require more control blocks to process than the transaction request B due to the complexity of the request. When enough control blocks needed to process transaction request B become available within the 31-bit storage, transaction queuing program 412 (FIG. 4) may transmit transaction request B to the 31-bit storage system for processing regardless of whether transaction request B was received by transaction request program 412 (FIG. 4) before transaction request A.

Next at 516, transaction queuing program 412 (FIG. 4) processes the transmitted transaction request. Once transaction queuing program 412 (FIG. 4) transmits the stored transaction request from the queue within 64-bit storage to 31-bit storage, the transaction request may be processed in accordance with standard techniques. For example, when a transaction request corresponding to a user's online purchase of a product from an online retailer is transmitted to 31-bit storage from the queue within 64-bit storage, the transaction request may be processed by debiting the user's credit card and crediting the online retailer's account.

It may be appreciated that FIG. 5 provides only an illustration of one implementation and does not imply any limitations with regard to how different embodiments may be implemented. Many modifications to the depicted environments may be made based on design and implementation requirements.

FIG. 6 is a block diagram 600 of internal and external components of computer 410 (FIG. 4) and server 420 (FIG. 4) depicted in FIG. 4 in accordance with an embodiment of the present invention. It should be appreciated that FIG. 6 provides only an illustration of one implementation and does not imply any limitations with regard to the environments in which different embodiments may be implemented. Many modifications to the depicted environments may be made based on design and implementation requirements.

Data processing system 602, 604 is representative of any electronic device capable of executing machine-readable program instructions. Data processing system 602, 604 may be representative of a smart phone, a computer system, PDA, or other electronic devices. Examples of computing systems, environments, and/or configurations that may represented by data processing system 602, 604 include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, network PCs, minicomputer systems, and distributed cloud computing environments that include any of the above systems or devices.

User client computer 410 (FIG. 4) and network server 420 (FIG. 4) may include respective sets of internal components 602 a,b and external components 604 a,b illustrated in FIG. 6. Each of the sets of internal components 602 include one or more processors 620, one or more computer-readable RAMs 622 and one or more computer-readable ROMs 624 on one or more buses 626, and one or more operating systems 628 and one or more computer-readable tangible storage devices 630. The one or more operating systems 628 and transaction queuing program 412 (FIG. 4) in network server 420 (FIG. 4) are stored on one or more of the respective computer-readable tangible storage devices 630 for execution by one or more of the respective processors 620 via one or more of the respective RAMs 622 (which typically include cache memory). In the embodiment illustrated in FIG. 6, each of the computer-readable tangible storage devices 630 is a magnetic disk storage device of an internal hard drive. Alternatively, each of the computer-readable tangible storage devices 630 is a semiconductor storage device such as ROM 624, EPROM, flash memory or any other computer-readable tangible storage device that can store a computer program and digital information.

Each set of internal components 602 a,b also includes a R/W drive or interface 632 to read from and write to one or more portable computer-readable tangible storage devices 638 such as a CD-ROM, DVD, memory stick, magnetic tape, magnetic disk, optical disk or semiconductor storage device. A software program, such as transaction queuing program 412 (FIG. 4), can be stored on one or more of the respective portable computer-readable tangible storage devices 638, read via the respective R/W drive or interface 632 and loaded into the respective hard drive 630.

Each set of internal components 602 a,b also includes network adapters or interfaces 636 such as a TCP/IP adapter cards, wireless Wi-Fi interface cards, or 3G or 4G wireless interface cards or other wired or wireless communication links. Software program 408 (FIG. 4) in client computing device 410 (FIG. 4) and transaction queuing program 412 (FIG. 4) in network server 420 (FIG. 4) can be downloaded to client computer 410 (FIG. 4) and network server 420 (FIG. 4) from an external computer via a network (for example, the Internet, a local area network or other, wide area network) and respective network adapters or interfaces 636. From the network adapters or interfaces 636, software program 408 (FIG. 4) in client computing device 410 (FIG. 4) and transaction queuing program 412 (FIG. 4) in network server 420 (FIG. 4) are loaded into the respective hard drive 630. The network may comprise copper wires, optical fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers.

Each of the sets of external components 604 a,b can include a computer display monitor 644, a keyboard 642, and a computer mouse 634. External components 604 a,b can also include touch screens, virtual keyboards, touch pads, pointing devices, and other human interface devices. Each of the sets of internal components 602 a,b also includes device drivers 640 to interface to computer display monitor 644, keyboard 642, and computer mouse 634. The device drivers 640, R/W drive or interface 632 and network adapter or interface 636 comprise hardware and software (stored in storage device 630 and/or ROM 624).

It is understood in advance that although this disclosure includes a detailed description on cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, embodiments of the present invention are capable of being implemented in conjunction with any other type of computing environment now known or later developed.

Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service's provider.

Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.

Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported providing transparency for both the provider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer is to use the provider's applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based e-mail). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds).

A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure comprising a network of interconnected nodes.

Referring now to FIG. 7, illustrative cloud computing environment 50 is depicted. As shown, cloud computing environment 50 comprises one or more cloud computing nodes 10 with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone 54A, desktop computer 54B, laptop computer 54C, and/or automobile computer system 54N may communicate. Nodes 10 may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as Private, Community, Public, or Hybrid clouds as described hereinabove, or a combination thereof. This allows cloud computing environment 50 to offer infrastructure, platforms and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices 54A-N shown in FIG. 7 are intended to be illustrative only and that computing nodes 10 and cloud computing environment 50 can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser).

Referring now to FIG. 8, a set of functional abstraction layers 800 provided by cloud computing environment 50 (FIG. 7) is shown. It should be understood in advance that the components, layers, and functions shown in FIG. 8 are intended to be illustrative only and embodiments of the invention are not limited thereto. As depicted, the following layers and corresponding functions are provided:

Hardware and software layer 60 includes hardware and software components. Examples of hardware components include: mainframes 61; RISC (Reduced Instruction Set Computer) architecture based servers 62; servers 63; blade servers 64; storage devices 65; and networks and networking components 66. In some embodiments, software components include network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers 71; virtual storage 72; virtual networks 73, including virtual private networks; virtual applications and operating systems 74; and virtual clients 75.

In one example, management layer 80 may provide the functions described below. Resource provisioning 81 provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and Pricing 82 provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may comprise application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. User portal 83 provides access to the cloud computing environment for consumers and system administrators. Service level management 84 provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment 85 provide pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA.

Workloads layer 90 provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation 91; software development and lifecycle management 92; virtual classroom education delivery 93; data analytics processing 94; transaction processing 95; and transaction queuing 96. Transaction queuing may relate to storing transaction requests in 64-bit storage when 31-bit storage is otherwise unavailable to process transaction requests.

The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein. 

What is claimed is:
 1. A processor-implemented method for queuing a transaction request, the method comprising: receiving, by a processor, the transaction request from a transaction processing system on a transaction server, wherein the transaction server manages application and database transactions on a network within a distributed computing environment; storing the received transaction request in a single queue within a 64-bit storage system, wherein storing the received transaction request in the 64-bit storage system occurs when a 31-bit storage system is unavailable to process the received transaction request, wherein the 31-bit storage system being unavailable occurs when the 31-bit storage system is offline, wherein the single queue includes the stored transaction request; and in response to a control block within the monitored 31-bit storage system being available, transmitting the stored transaction request from the 64-bit storage system to the monitored 31-bit storage system based on determining the control block is available, wherein transmitting the stored transaction request prioritizes transmitting a transaction request with a fewest total number of control blocks needed to process over transmitting a transaction request with a greatest total number of control blocks needed to process.
 2. The method of claim 1, wherein the received transaction request is received by a transaction server.
 3. The method of claim 1, wherein the 31-bit storage system is monitored for an availability to process the stored transaction request.
 4. The method of claim 1, wherein transmitting the stored transaction request is based on a total storage time for the stored transaction request.
 5. The method of claim 1, further comprising: processing the transmitted transaction request using the determined control block.
 6. A computer system for queuing a transaction request, the computer system comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising: receiving the transaction request from a transaction processing system on a transaction server, wherein the transaction server manages application and database transactions on a network within a distributed computing environment; storing the received transaction request in a single queue within a 64-bit storage system, wherein storing the received transaction request in the 64-bit storage system occurs when a 31-bit storage system is unavailable to process the received transaction request, wherein the 31-bit storage system being unavailable occurs when the 31-bit storage system is offline, wherein the single queue includes the stored transaction request; and in response to a control block within the monitored 31-bit storage system being available, transmitting the stored transaction request from the 64-bit storage system to the monitored 31-bit storage system based on determining the control block is available, wherein transmitting the stored transaction request prioritizes transmitting a transaction request with a fewest total number of control blocks needed to process over transmitting a transaction request with a greatest total number of control blocks needed to process.
 7. The computer system of claim 6, wherein the received transaction request is received by a transaction server.
 8. The computer system of claim 6, wherein the 31-bit storage system is monitored for an availability to process the stored transaction request.
 9. The computer system of claim 6, wherein transmitting the stored transaction request is based on a total storage time for the stored transaction request.
 10. The computer system of claim 6, further comprising: processing the transmitted transaction request using the determined control block.
 11. A computer program product for queuing a transaction request, the computer program product comprising: one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more tangible storage medium, the program instructions executable by a processor capable of performing a method, the method comprising: receiving the transaction request from a transaction processing system on a transaction server, wherein the transaction server manages application and database transactions on a network within a distributed computing environment; storing the received transaction request in a single queue within a 64-bit storage system, wherein storing the received transaction request in the 64-bit storage system occurs when a 31-bit storage system is unavailable to process the received transaction request, wherein the 31-bit storage system being unavailable occurs when the 31-bit storage system is offline, wherein the single queue includes the stored transaction request; and in response to a control block within the monitored 31-bit storage system being available, transmitting the stored transaction request from the 64-bit storage system to the monitored 31-bit storage system based on determining the control block is available, wherein transmitting the stored transaction request prioritizes transmitting a transaction request with a fewest total number of control blocks needed to process over transmitting a transaction request with a greatest total number of control blocks needed to process.
 12. The computer program product of claim 11, wherein the received transaction request is received by a transaction server.
 13. The computer program product of claim 11, wherein the 31-bit storage system is monitored for an availability to process the stored transaction request.
 14. The computer program product of claim 11, wherein transmitting the stored transaction request is based on a total storage time for the stored transaction request.
 15. The computer program product of claim 11, further comprising: processing the transmitted transaction request using the determined control block. 